In this article, an adaptive tracking control approach is developed for a class of strict-feedback nonlinear systems with time-varying full state constraints. As a breakthrough in this system, the special function constraints (whose constraint boundary is relevant to both state variables and time) are considered, which are rarely studied by research work. And there is no doubt that this method increases the complexity of designing this scheme. Furthermore, the time-varying integral barrier Lyapunov functions combining with backstepping technique is introduced to break the limitation of traditional methods as well as achieve the full state constraints. Meanwhile, fuzzy logic systems are selected to approximate unknown nonlinear functions. It is verified that all closed-loop signals are bounded and all states are forced in the time-varying boundness. In addition, the proposed control strategy has a good performance. The effectiveness of the theoretical analysis results is proved via a simulation example.

中文翻译：

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基于时变IBLF的函数约束非线性系统自适应模糊控制


在本文中，针对一类具有时变全状态约束的严格反馈非线性系统开发了一种自适应跟踪控制方法。作为该系统的突破，考虑了特殊函数约束（其约束边界与状态变量和时间都相关），这在研究工作中很少被研究。并且毫无疑问，这种方法增加了设计该方案的复杂度。此外，引入时变积分势垒Lyapunov函数与反步技术相结合，打破了传统方法的局限性，实现了全状态约束。同时，选择模糊逻辑系统来逼近未知的非线性函数。验证了所有闭环信号都是有界的，并且所有状态都强制处于时变有界内。此外，所提出的控制策略具有良好的性能。通过仿真算例证明了理论分析结果的有效性。